Director of Product Management -Product Platform

Nimbus Data Systems is transforming the way companies plan, manage, and optimize the models that run their business. We started by revolutionizing incentive compensation management, expanded into sales planning, and are building a unified, AI-native platform for the most critical models an enterprise runs. Recognized by industry analysts like Forrester and G2 and backed by top-tier investors including Sequoia, ICONIQ, Accel, Sapphire Ventures, and Workday Ventures, we power high-growth innovators like Figma, Stripe, and Snowflake alongside global enterprises such as Netflix, Mastercard, and Boston Scientific. Join a talented, fast-growing team committed to solving some of the most complex and impactful problems in enterprise modeling — at platform scale. About the Role Nimbus Data Systems is looking for a Director of Product Management to lead the strategy and execution of our Product Platform — the shared foundation that every Nimbus Data Systems application is built on. This is the connective tissue of the company: the layers that turn a set of products into a single, AI-native system. It is where data becomes connected and queryable, where workflows orchestrate long-running human-and-agent processes, where reporting turns models into decisions, where identity and entitlements govern who can do what, where state is versioned and audited, and where the AI and agent platform gives every product a consistent, agent-accessible surface. This role owns one of Nimbus Data Systems ’s highest-leverage areas. A single great primitive shipped here compounds across every product. It demands a leader who is hands-on, deeply curious about the systems beneath the surface, and capable of balancing rigorous platform thinking with decisive product execution. Job Location Midwest, East Coast, including Toronto, Canada. What You'll Own The Product Platform spans the shared layers and cross-cutting capabilities that sit between our applications and our infrastructure. Concretely, this scope includes: AI & Agent Platform. The agent SDK, MCP server (the single inbound surface for tool calls across the platform), agent portal for authoring and observability, eval framework and runner, and the shared chat/agent UI primitives every product embeds. This vertical spans the full stack — every layer must be API-first and agent-accessible. Data Platform. Bi-directional data connectors (ingest from HRIS, CRM, and more; egress to warehouse and BI), and the ETL / ingestion and transformation layer that takes raw third-party data through to clean, typed, queryable objects. Workflows & Reporting. Long-running orchestration with human-in-the-loop approvals (payout processing, plan rollout, period close), and in-house reporting and analytics built natively on platform objects and modeling outputs. Identity. Authentication and SSO, policies and permissions (RBAC, scoping enforced at every layer boundary), entitlements that drive feature gating, billing, org settings, and user preferences. State Platform. State as a first-class primitive — the versioning and state-transition machine every change flows through — plus the sandbox (branchable, isolated workspaces for staging changes safely) and audit (a record of every state transition for review and compliance) built on top of it. Your job is everything that makes our customer-facing applications interoperable, governable, and agent-ready. Responsibilities Own the Product Platform strategy and roadmap. Define how Nimbus Data Systems ’s shared layers — data, workflows, reporting, identity, state, and the AI/agent platform — evolve to make every product faster to build and every model more connected. Make the platform an accelerant, not a tax. A platform team succeeds only when product teams move faster because of it. Build primitives teams reach for by default, and retire the temptation to invent parallel versions. Champion interface-first, agent-ready design. Every platform surface must be designed API-first with well-defined schemas and documentation, with human UX built on top. Agents are only as reliable as the APIs and data structures they operate on — your layers are that substrate. Model hands-on product leadership. Stay close to the details. Immerse yourself in customer workflows, data models, agent behavior, and technical constraints. Reason from system dynamics, not surface requirements. Scale enterprise readiness. Deliver the governance, auditability, access control, sandboxing, performance, and reliability that enterprises operating at scale depend on — and that make AI-generated logic trustworthy and governable. Develop system thinkers. Coach PMs to think holistically across components and personas, reason about trade-offs, and make clear, structured decisions grounded in how the whole platform behaves. Drive measurable impact. Connect platform work to company-level outcomes — development velocity, API-first coverage, cross-model data flows, reduction in fragmentation — and ensure alignment through clarity, not control. Wha